Emerging longitudinal findings challenge the long-held contention that affective well-being increases uniformly across the life span. To date, little systematic empirical and theoretical work has established the boundary conditions within which well-being is enhanced or compromised in aging adults. The proposed research program intends to fill this gap by addressing 3 core questions that are essential to understanding the aging of well-being concerning: (1) how aging differentially affects distinct temporal measures of affective well-being (e.g., emotional reactivity; variability in emotional experience; short-term recalled emotional experiences); (2) characteristics of the psychosocial environment that may modulates these effects differentially by age; and (3) how varying aspects of experienced well-being differentially relate to perceived and objective physical health across the adult life span. The proposed project addresses these questions by applying a novel theoretical model (Strength and Vulnerability Integration; SAVI) to two longitudinal data sets. SAVI is the first theory that applies a principled account of when and under what circumstances age-graded increases will and will not be observed. SAVI predicts that the age-related positive memory bias documented in the literature largely accounts for findings of higher experienced well-being with age. This effect, however, can be minimized or eliminated in assessments of relatively proximal emotional states, and when people are given a contextual anchor (e.g., when recalling a specific event). The first dataset includes two waves of the Midlife in the United States (MIDUS) survey and the National Study of Daily Experiences (NSDE). Multiple aspects of well-being are assessed across 10 years among a large national sample of people spanning 50 years of adulthood, and biomarkers were collected at Time 2. The second data set will include the first burst of data from the Effects of Stress on Cognitive Aging, Physiology, and Emotion (ESCAPE) study, which consists of momentary sampling throughout the day across 14 days, nightly, weekly and a monthly assessment of emotional experiences, and biomarkers including those related to inflammation. These data capture multiple aspects of current and overall affective well-being and self-reported and objective health indices. The proposed project combines the theoretical innovations of SAVI with the methodological innovations of these data sets to test core questions about age, well-being and physical health. Knowledge gained will help inform future clinical intervention and prevention efforts by explaining these age-related and methodological dynamics and how they are related to health-related outcomes.